Unnesting/rectangling/flattening a nested list using `tidyr::unnest_longer()`

I've been trying to get my head around the unnesting functions in tidyr and tibblify. I believe you should be able to use unnest_longer() to replicate the more manual methods below of turning this kind of nested list into a tibble, but I've been struggling with the docs a little. A correct example of how to do this would help me immensely:

# Example nested list
nl <- list(time = list("2023-02-06", "2023-02-07", "2023-02-08",
                       "2023-02-09", "2023-02-10", "2023-02-11",
                       "2023-02-12"), 
           precipitation_sum = list(0.9, 0, 0, 0.3, 0, 0, 0))

# one way to do it (extract colnames and construct)
tibble(!!! setNames(map(nl, unlist),names(nl)))

# another way (collect & reduce each sublist)
as_tibble(lapply(nl, function(x) Reduce(c, x)))

# how to use tidyr and unnest_longer? (below is incorrect)
unnest_longer(tibble(nl), col = everything())

We could use

library(tibble)
library(tidyr)
as_tibble(nl) %>% 
    unnest(cols = where(is.list))

-output

# A tibble: 7 × 2
  time       precipitation_sum
  <chr>                  <dbl>
1 2023-02-06               0.9
2 2023-02-07               0  
3 2023-02-08               0  
4 2023-02-09               0.3
5 2023-02-10               0  
6 2023-02-11               0  
7 2023-02-12               0  

Or more compactly

library(purrr)
map_dfc(nl, unlist)
# A tibble: 7 × 2
  time       precipitation_sum
  <chr>                  <dbl>
1 2023-02-06               0.9
2 2023-02-07               0  
3 2023-02-08               0  
4 2023-02-09               0.3
5 2023-02-10               0  
6 2023-02-11               0  
7 2023-02-12               0  

Another intersting option is to use dmap (and the history behind dmap):

'purrrlyr contains some functions that lie at the intersection of purrr and dplyr. They have been removed from purrr in order to make the package lighter and because they have been replaced by other solutions in the tidyverse.' <https://github.com/hadley/purrrlyr/>

#install.packages("purrrlyr")
library(purrrlyr)
nl %>% 
  dmap(unlist)

  time       precipitation_sum
  <chr>                  <dbl>
1 2023-02-06               0.9
2 2023-02-07               0  
3 2023-02-08               0  
4 2023-02-09               0.3
5 2023-02-10               0  
6 2023-02-11               0  
7 2023-02-12               0